high performance computing on graphics processing units: hgpu.org

The diversity of microarchitecture designs in heterogeneous computing systems allows programs to achieve high performance and energy efficiency, but results in substantial software re-development cost for each type or generation of hardware. To mitigate this cost, a performance portable programming system is required. One fundamental difference between architectures that makes performance portability challenging is the hierarchical organization of their computing elements. To address this challenge, we introduce TANGRAM, a kernel synthesis framework that composes architecture-neutral computations and composition rules into high-performance kernels customized for different architectural hierarchies. TANGRAM is based on an extensible architectural model that can be used to specify a variety of architectures. This model is coupled with a generic design space exploration and composition algorithm that can generate multiple composition plans for any specified architecture. A custom code generator then compiles these plans for the target architecture while performing various optimizations such as data placement and tuning. We show that code synthesized by TANGRAM for different types and generations of devices achieves no less than 70% of the performance of highly optimized vendor libraries such as Intel MKL and NVIDIA CUBLAS/CUSPARSE.